PROJECT SUMMARY The Center for Medicare and Medicaid Services Quality Payment Program is designed to motivate healthcare providers to adhere to best practices in clinical healthcare and patient safety. Unfortunately, extracting quality measures data from the clinical record is burdensome and as such, participation among clinical healthcare providers is suboptimal. Our aim is to develop a system to facilitate automatic extraction of quality data. This will reduce the burden of data collection and help remove the barrier to participation that keeps more providers from participating in the program. The proposed project, titled ?Using advanced natural language processing to facilitate documentation of meaningful use and quality payment compliance?, aims to develop novel natural language processing methods to recognize key elements from the clinical notes to enable proper documentation of meaningful use and compliance with quality payment. We envision this to be an effective research partnership that leverages the complementary assets of SaferMD, a small business unit, and the University of Michigan, a non-profit research institution, to develop and evaluate a prototype tool to extract clinical quality measures data, and increase participation in the Quality Payment Program.